## What is/are Weighted Risk?

Weighted Risk - Starting from a published RPPA-based seven-protein signature of receptor tyrosine kinase (RTK) pathway activity in the form of an unweighted sum of the seven protein measurements, shown to have prognostic value in a 445-patient renal clear cell carcinoma cohort (TCGA-KIRC), we demonstrated that strong stratification of patients into high and low risk groups can be achieved by using a statistical approach—LASSO regression—with no a priori biological knowledge, to select from the 233 proteins and optimally combine their RPPA measurements into a weighted risk score.^{[1]}20%); inverse probability-weighted risk ratio 1.

^{[2]}Based on the regression coefficients a weighted risk score was created.

^{[3]}A weighted risk score incorporating age and ejection fraction was used to stratify patients into low-, medium-, and high-risk groups.

^{[4]}A meta-analysis with inverse-variance, random-effects modelling was used to estimate a mean, weighted risk ratio effect size measure of vaccine uptake.

^{[5]}Results: The method yielded similar 2-year effectiveness estimates for the full-series protocols; weighted risk difference estimates comparing unvaccinated children to those adherent to either full-series (two-dose RV1, three-dose RV5) corresponded to four fewer hospitalizations and 12 fewer ED visits over the 2-year period per 1,000 children.

^{[6]}The Mosquito Model also predicted a decrease in risk in current high-risk areas, with an overall reduction in the population-weighted relative risk (but an increase in area-weighted risk).

^{[7]}Risk ratios were obtained using a modified Poisson regression and weighted risk differences using binomial regression.

^{[8]}We used data from non-hospitalised SARS-CoV-2-positive and matched SARS-CoV-2-negative individuals from 2 weeks to 6 months after a SARS-CoV-2 test to obtain propensity score-weighted risk differences (RDs) and risk ratios (RRs) for initiation of 14 drug groups and 27 hospital diagnoses indicative of potential post-acute effects.

^{[9]}We further generate a number of price paths for the original index, the modified index and their components, according to a Dynamic Conditional Correlation GARCH specification, to assess the efficiency of the index weighted risk contribution scheme.

^{[10]}The methods range from a simple dichotomous or count scores to those quantifying as weighted risks such as the Family history density (FHD) measures.

^{[11]}This study aimed to establish weighted risk models for determining DFU occurrence and severity in diabetic patients.

^{[12]}Results: The baseline model comprised of CD33+CD14+ monocytes, Double Negative B cells and age, in a weighted risk signature which predicted PFS with a concordance index (C-index) of 0.

^{[13]}Compared with controls, the weighted risk of AF was increased by 11% (hazard ratio = 1.

^{[14]}By contrast, difficulty to access the site, environmental factors and pollution were found to be low-weighted risks with the least likelihood of occurrence.

^{[15]}The results showed that risk in marketing chain got the highest priority to be controlled since the greatest potential failure occurred in this channel with the weighted Risk Priority Number about 647.

^{[16]}The ideal solutions centered on the creation of a predictive analytic tool that would help social service providers determine who is most likely, based on a set of weighted risk factors, to engage in gun violence.

^{[17]}We show the superiority of this weighted risk, using both simulated data and an empirical control: air-temperature prediction in France.

^{[18]}The highest quartile group (≥75th percentile) of weighted risk score had approximately 12.

^{[19]}52% of patients starting domperidone; weighted risk ratio 2.

^{[20]}The model input variables include information related to the epidemic status and trends in clinical practice patterns of the target clinic, regional epidemic metrics, and the distance-weighted risk estimates of adjacent dialysis units.

^{[21]}Area under receiver operating characteristic curve using weighted risk scores (effect estimates) showed substantial strength for model comprising TRD + GATA (AUC = 0.

^{[22]}CONCLUSIONS We present a score integrating multiple appropriately weighted risk factors to identify the subgroup of patients with rTOF who are at high annual risk of death who may benefit from targeted therapy.

^{[23]}We empirically test advanced reward-risk parity strategies and compare their performance with an equally-weighted risk portfolio in various asset universes.

^{[24]}In this study, an integrated mathematical model with analytical hierarchy method and failure mode and effect analysis is proposed that will maximize the weighted risk reduction amount by considering the budget and time constraints of the companies at the same time.

^{[25]}The identified risk factors were incorporated in weighted risk scoring models to allow the quantification of the risk of HIV acquisition.

^{[26]}Binary riskscapes resulted in a limited understanding of the impact of features related to landslide riskscapes, but both ranked and human-factor weighted riskscape models provided more details to inform policy and plan for response to landslide events.

^{[27]}The encountered failure modes are then prioritized with respect to the previously weighted risk parameters.

^{[28]}The total weighted risk score at a cut-off > 2 showed a significant good power of discrimination (area under the curve = 0.

^{[29]}

## weighted risk score

Starting from a published RPPA-based seven-protein signature of receptor tyrosine kinase (RTK) pathway activity in the form of an unweighted sum of the seven protein measurements, shown to have prognostic value in a 445-patient renal clear cell carcinoma cohort (TCGA-KIRC), we demonstrated that strong stratification of patients into high and low risk groups can be achieved by using a statistical approach—LASSO regression—with no a priori biological knowledge, to select from the 233 proteins and optimally combine their RPPA measurements into a weighted risk score.^{[1]}Based on the regression coefficients a weighted risk score was created.

^{[2]}A weighted risk score incorporating age and ejection fraction was used to stratify patients into low-, medium-, and high-risk groups.

^{[3]}The highest quartile group (≥75th percentile) of weighted risk score had approximately 12.

^{[4]}Area under receiver operating characteristic curve using weighted risk scores (effect estimates) showed substantial strength for model comprising TRD + GATA (AUC = 0.

^{[5]}The total weighted risk score at a cut-off > 2 showed a significant good power of discrimination (area under the curve = 0.

^{[6]}

## weighted risk ratio

20%); inverse probability-weighted risk ratio 1.^{[1]}A meta-analysis with inverse-variance, random-effects modelling was used to estimate a mean, weighted risk ratio effect size measure of vaccine uptake.

^{[2]}52% of patients starting domperidone; weighted risk ratio 2.

^{[3]}

## weighted risk difference

Results: The method yielded similar 2-year effectiveness estimates for the full-series protocols; weighted risk difference estimates comparing unvaccinated children to those adherent to either full-series (two-dose RV1, three-dose RV5) corresponded to four fewer hospitalizations and 12 fewer ED visits over the 2-year period per 1,000 children.^{[1]}Risk ratios were obtained using a modified Poisson regression and weighted risk differences using binomial regression.

^{[2]}We used data from non-hospitalised SARS-CoV-2-positive and matched SARS-CoV-2-negative individuals from 2 weeks to 6 months after a SARS-CoV-2 test to obtain propensity score-weighted risk differences (RDs) and risk ratios (RRs) for initiation of 14 drug groups and 27 hospital diagnoses indicative of potential post-acute effects.

^{[3]}

## weighted risk factor

The ideal solutions centered on the creation of a predictive analytic tool that would help social service providers determine who is most likely, based on a set of weighted risk factors, to engage in gun violence.^{[1]}CONCLUSIONS We present a score integrating multiple appropriately weighted risk factors to identify the subgroup of patients with rTOF who are at high annual risk of death who may benefit from targeted therapy.

^{[2]}